#' Create temperature plots to display status and trend.
#'
#'
#' @param data Dataframe to determine status from. Must have 'excursion' column generated.
#' @param seaKen Results of Seasonal Kendall Analysis
#' @param station The station to plot
#' @param max_date The max date to show on the plot
#' @return dataframe of stations with sufficient data
#' @export
#' @examples
#' plot_temperature(data = data.frame, seaKen, station)
plot_temperature <- function(data, seaKen, station, max_date = min(data$sample_datetime, na.rm = TRUE)){
# obtain data range limits for plotting
result_max <- max(c(data$Result_cen, data$temp_crit), na.rm = TRUE)
xmin <- min(data$sample_datetime, na.rm = TRUE)
xmax <- max_date
ymin <- 0
ymax <- ifelse(result_max > 26, result_max * 1.1, 26)
data$excursion <- dplyr::if_else(data$excursion_cen == 1, "Excursion", "Result") # change numeric value to descriptor
if(all(is.na(data$excursion))){
data$excursion <- "Result"
}
# obtain plotting values for trend line if applicable
if(NROW(seaKen) > 0){
if(station %in% seaKen$MLocID){
slope <- round(seaKen[seaKen$MLocID == station & seaKen$Char_Name == "Temperature, water", "slope"], digits=3)
trend <- seaKen[seaKen$MLocID == station & seaKen$Char_Name == "Temperature, water", "trend"]
p_val <- round(seaKen[seaKen$MLocID == station & seaKen$Char_Name == "Temperature, water", "p_value"], digits=3)
x_delta <- as.numeric((xmax-xmin)/2)
y_median <- median(data$Result_cen, na.rm = TRUE)
sk_min <- y_median - x_delta*slope/365.25
sk_max <- y_median + x_delta*slope/365.25
}
} else {seaKen <- data.frame()}
p <- ggplot2::ggplot(data)
if(any(data$Spawn_type == "Spawn")){
# Convert spawning dates to datetimes
data$Start_spawn <- as.POSIXct(data$Start_spawn)
data$End_spawn <- as.POSIXct(data$End_spawn)
# create dataframe of spawning start/end dates, and relevant values for spawning period and criteria lines
spawn_zones <- unique(data[,c("Start_spawn", "End_spawn")])
spawn_zones$next_start <- spawn_zones$Start_spawn + years(1)
spawn_zones$y1 <- -Inf
spawn_zones$y2 <- Inf
spawn_zones$temp_crit <- unique(data$temp_crit)
spawn_zones$spawn_crit <- 13
# adjust plot limits to allow for first and last spawning period to plot
xmin <- min(xmin, min(spawn_zones$Start_spawn, na.rm = TRUE))
xmax <- max(xmax, max(spawn_zones$End_spawn, na.rm = TRUE))
# plot the shaded spawning period
p <- p + ggplot2::geom_rect(data = spawn_zones, aes(xmin=Start_spawn, xmax=End_spawn, ymin=ymin, ymax=ymax,
# linetype = 'Spawning Zone', shape = 'Spawning Zone', color = 'Spawning Zone',
fill='Spawning Period'),
color = NA, alpha=.2, show.legend = c(fill=TRUE, linetype=FALSE, shape=FALSE, color=FALSE))
# plot non-spawning criteria lines within non-spawning period
p <- p + ggplot2::geom_segment(data = spawn_zones,
aes(x=End_spawn, xend=next_start, y=temp_crit, yend=temp_crit,
color="Non-Spawning", linetype="Non-Spawning", shape="Non-Spawning"),
size = 1)
# plot spawning criteria lines within spawning period
p <- p + ggplot2::geom_segment(data = spawn_zones,
aes(x=Start_spawn, xend=End_spawn, y=spawn_crit, yend=spawn_crit,
color="Spawning", linetype="Spawning", shape="Spawning"),
size = 1)
} else if(any(!is.na(data$temp_crit))){
# plot non-spawining line across data if no spawning period apply
p <- p + ggplot2::geom_line(aes(x=sample_datetime, y=temp_crit, color="Non-Spawning", linetype="Non-Spawning", shape="Non-Spawning"))
}
title <- paste(station, unique(data$StationDes))
subtitle <- paste0("Assessment Unit: ", unique(data$AU_ID), " ", unique(data$AU_Name))
# plot data with excursion colors
p <- p + ggplot2::geom_point(aes(x=sample_datetime, y=Result_cen, color = excursion, linetype = excursion, shape = excursion)) +
ggplot2::ggtitle(title, subtitle = subtitle) +
ggplot2::ylab("7DADM Temperature (deg C)") +
ggplot2::xlab("Datetime")
# plot the trend line if applicable
if(station %in% seaKen$MLocID){
p <- p + ggplot2::geom_segment(aes(x=xmin, xend=xmax, y=sk_min, yend=sk_max, color = "Trend", linetype = "Trend", shape = "Trend"), lwd = 1) +
ggplot2::annotate("text", x = xmin, y = ymax, label = paste0("Trend Results: ", trend, ", Z-Stat: ", p_val, ", Slope: ", slope), hjust = 0, vjust = 0)
}
# apply color, shape, line types, and range limits
p <- p +
ggplot2::scale_color_manual(name = "",
values = c('Excursion' = 'red', 'Result' = 'black', "Trend" = 'blue', "Spawning" = 'black', "Non-Spawning" = 'black')) +
ggplot2::scale_linetype_manual(name = "",
values = c('Excursion' = 0, 'Result' = 0, "Trend" = 2, "Spawning" = 1, "Non-Spawning" = 1)) +
ggplot2::scale_shape_manual(name = "",
values = c('Excursion' = 4, 'Result' = 16, "Trend" = 32, "Spawning" = 32, "Non-Spawning" = 32)) +
ggplot2::scale_fill_manual(name = "", values = c("Spawning Period" = 'black')) +
ggplot2::ylim(c(ymin, ymax)) +
ggplot2::xlim(c(xmin, xmax)) +
ggplot2::scale_x_datetime(date_labels = "%b-%Y")+
ggplot2::theme_linedraw() +
ggplot2::theme(legend.position="bottom", legend.direction = "horizontal", legend.box = "horizontal",
panel.grid.major = element_line(color = "gray"),
panel.grid.minor = element_line(color = "gray"))
return(p)
}
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